We spot that the trend of worsening refinement continues for models under data shift as well. Similar to what we have already seen for LS, it also provides the lowest refinement performance under natural shift. A surprising observation to note is the poor performance of MX. MX as shown by [1]} performs well on out-of-distribution detection. However, when the data shift is not severe it appears that mixup provides no added benefit in terms of refinement.
